Merge pull request matplotlib#31313 from ayshih/round_half_down

Fixed lingering bugs with image rendering related to exact half display pixels

Author: QuLogic

lib/matplotlib/image.py

@@ -209,9 +209,15 @@ def _resample(
 
     # When an output pixel falls exactly on the edge between two input pixels, the Agg
     # resampler will use the right input pixel as the nearest neighbor.  We want the
-    # left input pixel to be chosen instead, so we flip the supplied transform.
+    # left input pixel to be chosen instead, so we flip the input data and the supplied
+    # transform.  If origin != 'upper', the transform will already include a flip in the
+    # vertical direction.
     if interpolation == 'nearest':
-        transform += Affine2D().translate(-out.shape[1], -out.shape[0]).scale(-1, -1)
+        transform = Affine2D().translate(-data.shape[1], 0).scale(-1, 1) + transform
+        data = np.flip(data, axis=1)
+        if image_obj.origin == 'upper':
+            transform = Affine2D().translate(0, -data.shape[0]).scale(1, -1) + transform
+            data = np.flip(data, axis=0)
 
     _image.resample(data, out, transform,
                     _interpd_[interpolation],
@@ -220,10 +226,6 @@ def _resample(
                     image_obj.get_filternorm(),
                     image_obj.get_filterrad())
 
-    # Because we flipped the supplied transform, we then flip the output image back.
-    if interpolation == 'nearest':
-        out = np.flip(out, axis=(0, 1))
-
     return out
 
 
@@ -408,7 +410,13 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
         magnified_extents = clipped_bbox.extents * magnification
         if ((not unsampled) and round_to_pixel_border):
             # Round to the nearest output pixel
-            magnified_bbox = Bbox.from_extents((magnified_extents + 0.5).astype(int))
+            # Add a tiny fudge amount to account for numerical precision loss
+            # on the two sides away from the Agg anchor point (x0, y1)
+            x0 = np.floor(magnified_extents[0] + 0.5)  # round half up
+            y0 = np.ceil(magnified_extents[1] - 0.5 - 1e-8)  # round half down
+            x1 = np.floor(magnified_extents[2] + 0.5 + 1e-8)  # round half up
+            y1 = np.ceil(magnified_extents[3] - 0.5)  # round half down
+            magnified_bbox = Bbox.from_extents([x0, y0, x1, y1])
         else:
             magnified_bbox = Bbox.from_extents(magnified_extents)
 

lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs.png

@@ -1677,6 +1677,8 @@ def test__resample_valid_output():
 @pytest.mark.parametrize("data, interpolation, expected",
     [(np.array([[0.1, 0.3, 0.2]]), mimage.NEAREST,
       np.array([[0.1, 0.1, 0.1, 0.3, 0.3, 0.3, 0.3, 0.2, 0.2, 0.2]])),
+     (np.array([[0.1, 0.2, 0.3, 0.4, 0.5, 0.6]]), mimage.NEAREST,
+      np.array([[0.1, 0.2, 0.2, 0.3, 0.4, 0.4, 0.5, 0.6, 0.6]])),
      (np.array([[0.1, 0.3, 0.2]]), mimage.BILINEAR,
       np.array([[0.1, 0.1, 0.15, 0.21, 0.27, 0.285, 0.255, 0.225, 0.2, 0.2]])),
      (np.array([[0.1, 0.9]]), mimage.BILINEAR,
@@ -1906,6 +1908,64 @@ def test_nn_pixel_alignment(nonaffine_identity):
             axs[i, j].hlines(seps, -1, N, lw=0.5, color='red', ls='dashed')
 
 
+@image_comparison(['alignment_half_display_pixels.png'], style='mpl20')
+def test_alignment_half_display_pixels(nonaffine_identity):
+    # All values in this test are chosen carefully so that many display pixels are
+    # aligned with an edge or a corner of an input pixel
+
+    # Layout:
+    # Top row is origin='upper', bottom row is origin='lower'
+    # Column 1: affine transform, anchored at whole pixel
+    # Column 2: affine transform, anchored at half pixel
+    # Column 3: nonaffine transform, anchored at whole pixel
+    # Column 4: nonaffine transform, anchored at half pixel
+    # Column 5: affine transform, anchored at half pixel, interpolation='hanning'
+
+    # Each axes patch is magenta, so seeing a magenta line at an edge of the image
+    # means that the image is not filling the axes
+
+    fig = plt.figure(figsize=(5, 2), dpi=100)
+    fig.set_facecolor('g')
+
+    corner_x = [0.01, 0.199, 0.41, 0.599, 0.809]
+    corner_y = [0.05, 0.53]
+
+    axs = []
+    for cy in corner_y:
+        for ix, cx in enumerate(corner_x):
+            my = cy + 0.0125 if ix in [1, 3, 4] else cy
+            axs.append(fig.add_axes([cx, my, 0.17, 0.425], xticks=[], yticks=[]))
+
+    # Verify that each axes has been created with the correct width/height and that all
+    # four corners are on whole pixels (columns 1 and 3) or half pixels (columns 2, 4,
+    # and 5)
+    for i, ax in enumerate(axs):
+        extents = ax.get_window_extent().extents
+        assert_allclose(extents[2:4] - extents[0:2], 85, rtol=0, atol=1e-13)
+        assert_allclose(extents % 1, 0.5 if i % 5 in [1, 3, 4] else 0,
+                        rtol=0, atol=1e-13)
+
+    N = 10
+
+    data = np.arange(N**2).reshape((N, N)) % 9
+    seps = np.arange(-0.5, N)
+
+    for i, ax in enumerate(axs):
+        ax.set_facecolor('m')
+
+        transform = nonaffine_identity + ax.transData if i % 4 >= 2 else ax.transData
+        ax.imshow(data, cmap='Blues',
+                  interpolation='hanning' if i % 5 == 4 else 'nearest',
+                  origin='upper' if i >= 5 else 'lower',
+                  transform=transform)
+
+        ax.vlines(seps, -0.5, N - 0.5, lw=0.5, color='red', ls=(0, (2, 4)))
+        ax.hlines(seps, -0.5, N - 0.5, lw=0.5, color='red', ls=(0, (2, 4)))
+
+        for spine in ax.spines:
+            ax.spines[spine].set_linestyle((0, (5, 10)))
+
+
 @image_comparison(['image_bounds_handling.png'], tol=0.006)
 def test_image_bounds_handling(nonaffine_identity):
     # TODO: The second and third panels in the bottom row show that the handling of

lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs_linear.png

@@ -589,8 +589,9 @@ class lookup_distortion
             if (dx >= 0 && dx < m_out_width &&
                 dy >= 0 && dy < m_out_height) {
                 const double *coord = m_mesh + (int(dy) * m_out_width + int(dx)) * 2;
-                *x = int(coord[0] * agg::image_subpixel_scale + offset);
-                *y = int(coord[1] * agg::image_subpixel_scale + offset);
+                // Add a tiny fudge amount to account for numerical precision loss
+                *x = int(coord[0] * agg::image_subpixel_scale + offset + 1e-8);
+                *y = int(coord[1] * agg::image_subpixel_scale + offset + 1e-8);
             }
         }
     }
@@ -780,10 +781,15 @@ void resample(
             params.affine.transform(&right, &top);
             if (left > right) { std::swap(left, right); }
             if (bottom > top) { std::swap(top, bottom); }
-            if (round(left) < left) { left = round(left); }
-            if (round(right) > right) { right = round(right); }
-            if (round(bottom) < bottom) { bottom = round(bottom); }
-            if (round(top) > top) { top = round(top); }
+            // Add a tiny fudge amount to account for numerical precision loss
+            int rleft = agg::iround(left - 1e-8);
+            int rright = agg::iround(right + 1e-8);
+            int rbottom = agg::iround(bottom - 1e-8);
+            int rtop = agg::iround(top + 1e-8);
+            if (rleft < left) { left = rleft; }
+            if (rright > right) { right = rright; }
+            if (rbottom < bottom) { bottom = rbottom; }
+            if (rtop > top) { top = rtop; }
             path.move_to(left, bottom);
             path.line_to(right, bottom);
             path.line_to(right, top);

lib/matplotlib/tests/baseline_images/test_image/alignment_half_display_pixels.png

@@ -80,6 +80,7 @@ class accurate_interpolator_affine_nn
     void begin(double x, double y, unsigned len)
     {
         m_len = len - 1;
+        m_cur = 0;
 
         m_stx1 = x;
         m_sty1 = y;
@@ -98,6 +99,7 @@ class accurate_interpolator_affine_nn
     void resynchronize(double xe, double ye, unsigned len)
     {
         m_len = len - 1;
+        m_cur = 0;
 
         m_trans->transform(&xe, &ye);
         m_stx2 = xe * subpixel_scale;
@@ -107,23 +109,30 @@ class accurate_interpolator_affine_nn
     //----------------------------------------------------------------
     void operator++()
     {
-        m_stx1 += (m_stx2 - m_stx1) / m_len;
-        m_sty1 += (m_sty2 - m_sty1) / m_len;
-        m_len--;
+        m_cur++;
     }
 
     //----------------------------------------------------------------
     void coordinates(int* x, int* y) const
     {
         // Truncate instead of round because this interpolator needs to
         // match the definitions for nearest-neighbor interpolation
-        *x = int(m_stx1);
-        *y = int(m_sty1);
+        if (m_cur == m_len)
+        {
+            *x = int(m_stx2);
+            *y = int(m_sty2);
+        }
+        else
+        {
+            // Add a tiny fudge amount to account for numerical precision loss
+            *x = int(m_stx1 + (m_stx2 - m_stx1) * m_cur / m_len + 1e-8);
+            *y = int(m_sty1 + (m_sty2 - m_sty1) * m_cur / m_len + 1e-8);
+        }
     }
 
 private:
     trans_type* m_trans;
-    unsigned m_len;
+    unsigned m_len, m_cur;
     double m_stx1, m_sty1, m_stx2, m_sty2;
 };
 #endif